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Title: Annual Budget with Scenario Planning: From Assumptions to a Board-Ready Model
Description:
Built an annual budget model with worst/base/best-case scenarios, driven by a small set of editable assumptions rather than hardcoded projections — designed to be reforecast quarterly against actuals without rebuilding the model each time.
Challenge: The business needed an annual budget the board could approve with confidence, but a single-point forecast hid how sensitive the outcome was to a handful of key assumptions — and any change meant rebuilding numbers from scratch.
Approach: Structured the budget around a small set of core drivers (revenue growth, cost ratios, headcount timing) that flow through to revenue, opex, EBITDA, and cash runway. Built worst/base/best cases as three versions of the same driver set, not three separate models, so scenarios stay consistent and auditable.
What I did: Designed the driver architecture, built the scenario toggle logic, and set up a quarterly reforecast cadence so actuals feed back into the model and next-quarter assumptions adjust automatically rather than through manual overrides.
Outcome: Gave the board a budget with visible downside and upside, not just a single number — and turned each quarterly review into a 30-minute update instead of a rebuild.
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Dashboard Key Highlights:
Total Performance: Total Revenue of $5,468 and Gross Profit of $2,313 with an overall profit margin of 42.3%.
Top Profit Contributor: Product D yields the highest gross profit at $1,548 (54.3% of total profit) and revenue of $2,808 (51.4% of total sales).
Highest Margin Product: Product A leads in efficiency with a 66.7% profit margin ($540 profit on $810 sales).
PROFESSIONAL SUMMARY
Data-driven professional with strong expertise in Data Analysis, Excel, and SQL. Proficient in building data dashboards, performing complex data cleaning, and deriving actionable business insights. Demonstrated ability to work with large datasets (1400+ records) and create comprehensive analytics solutions. Seeking part-time opportunities to leverage analytical skills while expanding expertise in data-driven decision-making.
TECHNICAL SKILLS
Data Analysis & Visualization: Excel (Advanced), SQL (Intermediate), Data Cleaning, Data Modeling
Excel Expertise: Advanced formulas, VLOOKUP, Pivot Tables, Dashboards, Data Validation, Conditional Formatting
SQL Skills: Query writing, Data extraction, Database analysis
Programming: Python (Basic).
Project Links :
an Excel-based data analysis project focused on Sales Performance and Employee Analysis.
🔹 Sales Analysis
• 50 sales records
• Product & category performance
• Regional sales analysis
• Total sales and order KPIs
• Date-based analysis
• Pivot Tables & charts
🔹 Employee Analysis
• 30 employee records
• Department & job-title analysis
• Salary analysis
• Years of experience
• Salary Rating & Experience Status
• VLOOKUP-based analysis
🛠️ Excel Skills Used
• Data Cleaning
• Formulas & Functions
• VLOOKUP
• Pivot Tables
• KPI Analysis
• Data Categorization
• Business Reporting
This project helped me practice turning raw business data into structured analysis and actionable insights.
Project Link : https://github.com/rajveer7489/sales-employee-analysis
